how to use normalization axis parameter when preprocessing data

sklearn.preprocessing.normalize(X, norm='l2', axis=1, copy=True, return_norm=False)

sklearn.preprocessing.scale(X, axis=0, with_mean=True, with_std=True, copy=True)

for normalize, axis=1 is the default option, but for scale, axis=0 is the dedault one.

I got confused when to use axis=0 or axis=1?